Who Owns the Data Behind the AI Boom in Market Research?

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AI money is pouring into market research, but who actually owns the data feeding it? Kerry Hecht and Lenny Murphy dig into Simile's $2B valuation, the C-suite shakeup at Ipsos, and why a $20M-funded AI interview startup might be chasing scale it can't verify.

Plus: why "guardrails" are becoming the industry's next battleground, and what it means when big companies start selling outcomes instead of software.

Thanks to our producer, Karley Dartouzos. 

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Transcript

Lenny Murphy: And we're live. Happy Friday, Kerry Hecht, our surprise guest host. So it's so cool to have you. For the listeners, Karen. Do what, Kerry? Sorry. Glad to be here. It's awesome to have you always. Karen is at the Market Research Council Hall of Fame event, luncheon in New York City, honoring John Gilfeather. Lisa Cortaid, whom we all know and love. Not to say we don't all know and love John. I don't know John, but he did do a great podcast with Karen earlier this week. Lisa Cordaid, John Bremer, and Jim Whaley, all great, great, wonderful people and friends of ours in the industry. So that's where Karen is today. We were supposed to pre-record yesterday. Things Murphy's Law kicked in. Kerry so graciously jumped in, even though you're out of town doing what, your brother's wedding, right?

Kerry Hecht: I'm coming to you from El Paso today. So, yes, the high desert.

Lenny Murphy: You know, that's a very El Paso shirt.

Kerry Hecht: So, oh, this is my new uniform. This is, we won't spend too much time on that, but this is my new uniform shirt. I switched gears from black to pink plaid.

Lenny Murphy: Okay. I like it. I like it. So also, not always a mad scramble to say, Kerry, please jump in, but also breaking news. And we don't normally have breaking news. Our workflows, we usually try to wrap this up Thursday evening. But then this morning was like, holy crap, there's two things we have to talk about. So I'll queue them up, Kerry, and we can talk through it. The first one is the, oh my God, raised by Simile. Simile raised, they just closed a 200 million Series B at a $2 billion valuation. And that's only five months from their 100 million Series A

Kerry Hecht: Yeah.

Lenny Murphy: And so the Reese Simony comes up a lot because remember they're their foundational models based off of Gallup. Yeah. Yeah. Right. So they are a very interesting company when they are taking, you know, they're taking research data, using that as a foundational model. Now they're doing a lot more with that now. I understand they're embedding themselves as infrastructure in organizations. To create digital twins, that is their play, digital twins, based off of this foundational piece of the out tracking data and other data sources, and then the customer data and using that as a predictive engine across the organization, not just for research for all types of stuff. But holy smokes, holy smokes, 200 million raised, $2 billion valuation within six months.

Kerry Hecht: Crazy. And I think that there's thematically gonna be two things here, right? So, one is this next generation of interactive models and how deep they can go. And we're gonna touch on that on a few other topics as well. But the other side of this, to your point, is this valuation. So, in talking to some tech founders over the course of the past few years, those kinds of high valuations can be a bit of a mixed bag, right?

Lenny Murphy: So, there's absolutely a lot of pressure.

Kerry Hecht: Yeah, what do they say? It's like chasing the dog chasing the bus, right? You know, you get it, and all of a sudden it's like, wow, this is amazing news, and now we have to live up to a two billion dollar valuation.

Lenny Murphy: So, and there's certainly been, you know, in the last few months, Medallia, Domo. Both come to mind, right? Big companies had, you know, massive raises, big valuations, and but weren't didn't align to the trajectory of the world, right? There comes a point where it's hard to pivot when you're doing that. We'll see.

Kerry Hecht: Well, it's also there's, there's the, you know, always. The first to market and then the followers, right? And in a space that's moving as quickly as all tech and all AI is moving now, primarily because it's powered by AI, right? So you could be the preeminent one for 15 minutes, and then you've got 15 other companies who maybe have a slightly different way of thinking or access to their own data that's somehow unique. Or you've got companies realizing that they don't need to spend money on the software. They can spin up their own engines and why pay for it. So, I mean, it's a really interesting space. And I mean, I think these, you know, these dollar amounts are just so astronomical, they're actually incomprehensible to an average Joe like me. So it is going to be interesting to see how this all plays out. And how much of it is a money grab, and how much of it turns into something that is a new and stable foundation.

Lenny Murphy: Right. Yes. Wonderful way to think about it. And it has so many that applies to so many businesses out there now. I mean, and at this level, I would say, you know, you're raising that much money at those types of valuations. You're going for an IPO that's. You're already out of reach for companies from an acquisition standpoint. Although, you know, it is my understanding of simile, and this isn't about, you know, simile, but it's out there. It's public. Let's use them as an example, right? That they are building the decision intelligence infrastructure off of digital twin data across the enterprise. It's not just research. And it is a mistake to think that this company is playing only in the research space. Certainly, there's some of that 100%. But that concept of who's infrastructure, right? And then who is a utility? I think that's you and who owns the data that's feeding the infrastructure.

Kerry Hecht: Yeah, we're not past who owns the data question. And I think that as people are realizing the asset that they have or the way an asset that they helped create that someone else is now using and selling, I think that there's going to be a lot more interesting conversations. Now. You know, it makes me think of the lime scooters, you know, like the lime scooters were dropped on every city in the country, and then people figured out that maybe they didn't want them until after that. So it's, I think there's going to be some of that where it's like companies are going to start selling data, and then the companies, other companies are like, wait a second, I think I might own that data. And yeah. And so I think there's, there's, I mean, it's going to be interesting to see how it plays out, or they're going to realize that. They don't want their data to be part of the machine, which is something, of course. We talked a little bit about the early days of large language models. But now that you're seeing people, you're seeing companies monetize it on the back of services that were provided a long time ago, I think it is going to be an interesting space. And there's also not much prevention. Lots of people who otherwise didn't have the technical skills or the budgets to create their own softwares. Now, all those tools have been democratized. So, anyone that's sitting on any kind of data now has the tools at hand where instead of spending hundreds of thousands, if not millions on development tools, you can just spend a month in a locked room by yourself and figure it out.

Lenny Murphy: Right. Well, you've been doing that, right? So, I mean, 10K, I know you and I talked, a while back and we were geeking out about vibe coding.

Kerry Hecht: And, you know, oh, yeah. Yeah. So, yeah. It's my new favorite thing. It's my new favorite thing because you can imagine ecosystems and then you can sit down and build them.

Lenny Murphy: Yeah. Yeah. Interesting times. Well, it's a theme that we will revisit as we go through all the other pieces. There was other breaking news just this morning on the change of CEO at Ipsos. So this was interesting to me because, well, interesting in a lot of ways, but then, you know, they just went through a change and brought in a senior person from Accenture. You know, who's definitely transforming the business. And we've seen that now, he's, he's accidentally pursuing other interests. Okay. We'll take it at face value. They just released results last week. And those results were good. So, so a little surprising of either, you know, they. Came in and banged it up and changed the business and said, All right, my job here is done and moved on. That's what he did. Or there's something else potentially at a kind of a macro level that Ipsos, the board is looking at and saying, this may not be the right leader, but from that, but they promote from within. So hats off to Kelly Beaver. I don't know Kelly, but she's been there since 2011 as the head of UK Public Affairs, becoming CEO of Ipsos UK in Ireland in 2021.

Kerry Hecht: So an internal promotion for her.

Lenny Murphy: And that just seems interesting to me if you bring in an external person who's changing up the business, and then that external person leaves, and then you're promoted back to somebody with their basis in research. I don't know. We'll see. I have zero insider knowledge, anything. It's just interesting to see that tension.

Kerry Hecht: Yeah, and we're going to talk more about the C-suite in market research later on in this episode. But I do think that there is, there's a lot of evidence that these roles are at a really high level. Are being redefined on the fly, right? And I also think that there's something to be said for, you know, and again, I'm hypothesizing, so I don't want to imply that I have any more information than the headline that was shared with me. You know, but that people can get into something and decide it isn't for them, you know, and so, or especially in these huge institutions, right? Like, you may come in as an agent of change and then realize that. Change moves more slowly than you're used to moving, and that you like a more nimble situation. So I think there's a million different ways this can play out, but it's not lost on me that anyone that's in C-suite right now is having to reinvent themselves and reinvent their organizations on the fly. And things are, you know. The roles are changing and then they're changing back and then they're changing again. And then, what does growth look like in an environment like this? And how do you know, a roadmap for the next five years when, you know, the next 15 minutes are different every 15.

Lenny Murphy: Yes. Yeah. I mean, the analogy I use is almost every company right now is, you know, they're rebuilding the plane in midair. Yeah. Yeah. In very turbulent air.

Kerry Hecht: Yeah, which can be really exciting. You know, it can be really exciting, but it can also be, especially when you're talking about a gigantic organization that historically has moved at the pace of a glacier. You know, that's a pretty big load. And I would imagine that you're, you know, you're, again, you're navigating a board, you're navigating employees, you're navigating your own, you know, there's a lot of moving parts there.

Lenny Murphy: It is well and and the issues like data ownership and technology and you know I mean these things that are now the old business models are not necessarily aligned to the current drivers of value creation um but yeah so interesting but on that note let's let's get into some of the the non-breaking news new news this week um the uh uh constellation uh bought delineate uh So hats off to them. Constellation is an interesting, you know, they're a buy and hold holding company.

Kerry Hecht: They buy software. I've never seen that. I was digging in. I was digging into them last night and I was like, oh, this is really interesting. And as a person that doesn't play in that space at any kind of level, that anyone would want to buy something, but I was surprised by that. I was like, oh, this is kind of cool. So you can go in. And you can, it's sort of different than getting VC investment, right? You know, so, um, but it still lets you retain the autonomy that you want. I thought that was a really interesting model.

Lenny Murphy: Yeah, it is. And they, uh, you know, they're, they're not usually premium payers. Um, I actually have had a few conversations with them over the years, and I know what they're looking for. And as I mean, it's not so, but the premium.

Kerry Hecht: Comes with premium expectations when maybe, you know, again, it assumes that everyone's, you know, everyone's goal is not going to be the same. People may just need a little more of a stable foundation in order to run.

Lenny Murphy: Right. 100%. And if you're the founder CEO, as in the case of Delineate, and you're just tired of carrying all the risk on your own. You know, a deal like Constellation, like, okay, now let's focus on just growing the business is a fantastic, fantastic way.

Kerry Hecht: And there's plenty of 100%.

Lenny Murphy: And Delineate does own proprietary data, right? So they've been building that for years. And so, so definitely something too. Kind of reinforce that, that thesis we saw in real time. So, this next one, definitely want to get your take on this, right?

Kerry Hecht: Coming from an opinion on this.

Lenny Murphy: Yeah, sure. I had not heard of this company truly. Well, the seed round, 20 million, 20 million seed round. For. 45-minute in-depth interviews. So rather than going for global scale, they were going for depth, AI-powered depth.

Kerry Hecht: Yes.

Lenny Murphy: Which I thought, now that is neat. They're looking, they're trying to power context.

Kerry Hecht: But give me the but Okay, so the but is that they are immediately also advertising the way that they do this with speed and at scale. Um, it is through the panel, right? And so, you know, they're immediately there, this, I think it's the second or third bullet point, um, that's here is that you know, we have access to 180 million people worldwide, you like everybody else, yeah, right. And so, so I didn't see, I thought the sales pitch was good, I didn't see the offering as really that distinct, but then when it comes to the participant pool. You know, you're right back to where everyone else is. And, which I think has implications, you know, there's a reason why qualitative companies do not use panels for qual because it doesn't work. And so we're in sort of a unique space in this because we love playing with the AI tools, but we're starting to get brought in because they're not getting the depth that they want to. So all of a sudden, you know, this better, faster, cheaper is actually not better. And then it's not cheaper because now you're having to recruit equal respondents. So, I think that made me raise an eyebrow. And it was like, look, I'm all for new tools and I'm excited. But I think that we are now at the point where we're seeing how some of this stuff plays out. So, that made me raise an eyebrow. And if I was getting a demo, that would be where my line of questioning went.

Lenny Murphy: Yeah. Every qual platform that has existed, right, all the way from the early stages of, you know, of online, virtual focus groups, et cetera, et cetera, have always run up against this issue.

Kerry Hecht: Yes. Yes.

Lenny Murphy: And the balance between the, to deliver on the promise of speed and efficiency, absolutely.

Kerry Hecht: Got it. Yeah.

Lenny Murphy: The balance with quality. That can be a challenge. And the panels have always struggled with it. Many have gone down the path of realizing, well, screw it, we just need to build a panel. My understanding is that Listen Labs right now, which has been kind of the high-growth hyperscaler, they're building their own panel.

Kerry Hecht: Yeah. They'll run into the same, you know, look, they'll run into, I mean, I think, I think people underestimate. How much work is involved in building a truly verified panel. Right? You're the expert on that. Yeah, yeah, and maintaining it. And so, I mean, you know, there's a lot of companies out there that I would say, you know, kind of hit the scene maybe 10 years ago. And when they were talking about, when they were building their panel, they were doing, you know, they were, they were. Posting advertisements, especially in the U.S., on places like Craigslist, right, and things like that. And they were getting people in, and you'd query them. You know, well, are these people verified? And well, there's too many people entering a day for us to verify them at the moment. So we rely on the clients to verify them. And so, you know, I mean, again, and it worked for them. There's a lot of people that made a lot of money, but I just think that it's one of those. You know, it's just not quite as simple as that, right? It just really isn't, especially if you're going to keep it verified.

Lenny Murphy: Right, right. And increasingly in this world, you know, I mean, it's always been, you know, garbage in, garbage out has been a truism, period. Sure. There's been a broken record on this, so you have two. Now, in the era of AI, look, take the example of a simile, all right? They're going to be infrastructure driving all the decision making across the business supporting that. And building digital twins that damn well better be good data, right? Because the risk of contamination is significant.

Kerry Hecht: So, yeah, I mean, these tech solutions, too, my understanding from talking to some of our clients about them is that when there are problems with the people, they get kind of routed in a circular way. So it's like, you know, the tech company is like, well, that's not our problem. And then the panel company. You know, or whoever doesn't get back to them in a meaningful way in the right timeframe. So, you know, it ends up, it can end up being a very frustrating experience for, you know, the researchers that are using them. And heaven forbid it's live and their client is watching. You know, I mean, so, so I think that there's, I think we, we, I mean, look, it's not going to stop or slow down based on what I say, but I do think that there is a reflection point that should happen right now that it's just like, look, we got to. We got to figure this out a little bit better, you know, at least that piece of it.

Lenny Murphy: And there's proof points in the market, right? The example that I use. Good Lord. It's been a long day.

Kerry Hecht: It's not ignored yet. I know.

Lenny Murphy: The guys out of the UK that built them have started out as basically a kind of mechanical turk business. Prolific. Yeah. Apologies, prolific team. I had nothing to do with you. It's just my brain getting old. I mean, you know, a couple months ago, the CEO said, hey, we've hit 500 million, the projected 500 million this year on a relatively small, only a couple hundred thousand high quality vetted. Panelists. They pay well. They are proving that, sure, there may be some scale challenges there. And let's recognize that, but they have certainly done well by focusing on quality.

Kerry Hecht: Yeah, there was a model that was several years back, and I won't rabbit hole too long on this, but just give me like 30 seconds. You know, where our industry has that tension between professional respondents and representative samples and things like this. And I think for some of these databases that need to grow larger in order to accommodate the scale, especially with AI qual, I think that we need to toss. The idea about professional respondents out the window. I think that we need to be comfortable with the fact that these participants know what they're going to do. They're comfortable with the fact that they understand they're making $150, so they need to show up or even $50, that they need to show up and do a good job and provide robust responses and things like that. So I think that we. You know, we would get ourselves a lot further if we didn't criticize the participants for looking at a way as a way to make reasonably good side hustle money. Um, yeah, and it has to be that way for AI qual, I think.

Lenny Murphy: I agree. Mean, at this. And now, that's interesting. So, all right, we're going down a rabbit hole on this a little bit because it is interesting. If you look at the no, no, because this is relevant, the companies. Those are basically panel companies that have provided AI training, right? Companies like Appen, Scale that were bought for a bajillion dollars by Meta. They are recruiting people to do tasks by their very nature. They have created a crowd, how they would call it, or their cloud or whatever, but it's a freaking panel. And they're paying people to do things. And that data was incredibly valuable and useful. And obviously, those companies have, you know, become very successful. When you do political polling, things like that, that's one thing. I totally 1% agree. So that a balanced census level, you know, not a census sample is. That's perfect. The ivory tower should be that way, if you can pull it off. So, but for the bulk of commercial research that is done, to your point, okay, these people, uh, as long as they're being honest, that's the you know, right?

Kerry Hecht: Yeah, then why the hell not?

Lenny Murphy: And we should be paying them fairly.

Kerry Hecht: Proliferate pays 15 bucks an hour, so yeah, and we're not monolithic consumers, you know what I mean? So, like, you know. Even if you think about yourself or yourself or anyone else that you talk to, you know, there are lots of things that they use in their lives that they are experts on. And if they understand the value proposition, you know, that's one of the things that we complain about all the time with bad data and bad participants is that they don't understand the value proposition. Well, for the most part, qualitative participants do. Right? So they understand that they're being paid, you know, a reasonably good amount of money and that they need to show up and do a good job. And so, you know, so if we can cultivate the people who are appropriate for that task, you know, to your point, that if we think about it as a task-based task, which I definitely think we should be. That we should be cultivating those people and continuing to, you know, every study that they participate in is another learning opportunity for them to know how to behave and how to deliver.

Lenny Murphy: You know, yeah, 100% agree. I think that we have to rethink, it's always about fit for purpose, right? Yeah, right. And one of Q Research was one of my first. When I hung out. Actually, they were my very first client when I hung out my shingle many years ago. That's a whole other story. The point was that it's sensory work, right? That was their claim of fame. And their panel, they wanted people who were really good smellers, right? So that they were reliant on them, you know, of like, okay, we know that this person can differentiate odor because we have to do a test for. Clorox. And we want it to. So their expertise was valued.

Kerry Hecht: Yeah, there was a company who, for the life of me, I cannot remember their name that I spoke to at a conference easily a decade ago, if not longer. And I hate the fact that I can't remember their name because they so influenced the way that I was thinking about particularly professional respondents. So they created a database that was exclusively professional respondents, and these people were. Taught how to think in an empathetic fashion. Taught to put themselves in other people's shoes. And they graded them initially on their creativity and their ability to think outside the box and so on and so forth. And then these folks were charging $1,500 a pop for access to these people who had been trained as professional respondents. So you could have a cop that scored really high. On, all the empathy scores and the creative thinking and everything else. And he would get in there and talk to you about kids' Legos, you know, because and I always thought that that was, not that every company needs to go all that way, but that we should be taking some of the really valuable ways to think about that.

Lenny Murphy: B2B panels, expert networks, you know, yes, the use cases are slightly different. 100 of you know guys letting in carry doing what the hell they're talking about with research no the use cases are different but I think that that is the argument is let's think about these that was always even when I you know was running rock hopper and we'd have a client come through with this screener you know we only want to target these titles now it always pushed back of like that is the wrong way to think about this yeah so we're never going to get those titles what you're looking for is responsibility let's rethink our screening criteria to get And look, if you've got 180 million people, circling back to the to truly, if you've

Kerry Hecht: Got 180 million people worldwide, you know, spend instead of using that as the, you know, because they're just tapping into an exchange, you know what I mean? 

Lenny Murphy: Like, that's right.

Kerry Hecht: Yeah, I'm sure it's in a perspective or something. Yes. I would be much more inclined to. Jump on that bandwagon if what they had actually said is of this 180 million people, we have verified and gotten articulation videos and already verified their IDs and dove deep into them. We know that they've completed similar kinds of projects successfully. So of that 180 million people, we have profiled 1.5 million. So we know that those 1.5 million are absolutely excellent, and we start with those people. If we need to go external to that because the sequence is too low, then we tap into the rest of it. But we start with these folks who we know are rock stars, right? Agreed. That's my sense of. Yeah, moving on.

Lenny Murphy: Moving on, there's two more. Uh, let's give a shout out to uh some funny news. Uh, we're because we're still there. Um Polybox and Fire AI, the Polybox 700,000 pounds, I should say, since it's weekend for AI-driven analytics on top of its real-time market data platform. And then Mumbai-based Fire AI raised 260,000 for its causal decision intelligence tool. So I think that they were working on some level of proprietary data or empowering proprietary data in a very specific way. We see it's investable, early stage. So it's great to see there's money flowing to these companies.

Kerry Hecht: Well, yeah, and further market intelligence tools, right? So additional market intelligence tools. And it goes to what we were talking about earlier: you're either going to be paid for access to data or for certain ways of thinking.

Lenny Murphy: Right. Yep. Yeah. Well. For that, you want to talk about discussing?

Kerry Hecht: Yeah. So this was, I dug deep into this last night because so discuss has launched a new product where basically they're giving clients access. The way that I'm understanding this is slightly different from what we've seen pop already with what Qualtrics was doing, but they're giving access to their clients. To the libraries of information that they've done over the course of you know however long their relationship was with discuss and that it's a queryable tool so it's basically just like you now have the ability to query um all of the work that you've done with us and you can you can you can um interact with it right and um which I think at the account level right I think to make clear it's not yeah right p and g can't use uh your levers yeah, right. Yeah, yeah, so that's which I think we have seen that pop up a few times already, and it does make you raise an eyebrow. So, I was glad to see that they were not doing that as well, right? Because that goes back to that data ownership question. Um, but I do think that this is again, this is a tool that you're going to see pop up. Oh, it's going to become a table stakes tool for anyone that is a data collector.

Lenny Murphy: You may already be there.

Kerry Hecht: I would agree. I mean, this is, you know, like, we're doing the same thing, right? You know what So it's, I think that this is going to be a table stakes tool. When I think about how long it's going to be a viable, sellable option, right, where you can sell access to it, I don't see that as being something that is going to be around for a long time because clients are just going to. Realize well, wait a second, I own this anyway. So why don't you just send me all of that? And then I'll just run our own customized agents that are already programmed for our way of thinking. You know, if we're a strategy agency, we've already programmed it to think like that, and we've trained it on our own models. So I don't, I think it's exciting. I think people should be doing it. I think that it's interesting. And I like the fact that it's making. Again, it's a democratization for small business owners, not that they're that small of a business, but it's also great for the client to be able to further utilize things from the past, et cetera, et cetera. Although they will get to a place where it's the same thing. So, if an agency, let's just say a market research agency, is accessing their data that way and learning from it, that becomes the same. Ethical question across their client base. Right. So I think, you know, we're, we're sort of always getting back to the same place. I don't know how much people are going to care about that ultimately. I don't know. But I think that it's, you know, there's, it's a great tool to have and good for them for developing it, you know, quickly. Yes. We'll see where we are in five years.

Lenny Murphy: Yes. Unlocking value of data in new ways. Yeah. If you've been a platform and you're housing client data, make that data liquid. Make it 100%. But to your point, that doesn't mean that you're going to be the only access point for that data. So we've talked for weeks. If you'd have been listening, but about NIQ. And we should always point out that, you know, Nielsen IQ is different from Nielsen Media. So they are two different things. There's kind of the purchase data and the media data. So Nielsen and Intel launched a whole new AI system that looks like they're going down the same path as their former cousin. Sibling, whatever the hell, of Niels IQ, of building a platform to unlock data, usability, utility, utilization, et cetera, et cetera, in new ways than they have before. So I actually was a little shocked when I was like, oh, they weren't already doing that. Okay. Well, good. Glad they're doing this now. Cause I just assumed they probably were.

Kerry Hecht: Yeah. This will be the other side of the table stakes, right? So it's like if you do have access to all of this public data, then you need to give people, you know, engines that are targeted on the way that they should be thinking about the data. So you need to do that work for them and the software that will do that, you know, and deliver it via MCP.

Lenny Murphy: So that headless piece, like somebody may log into the Nielsen portal to do this, or they may be using their own.

Kerry Hecht: Yeah, I like that. I actually like that. I thought that was really cool. Like, I was like, because again, if your point, if you're a research agency, your point of differentiation is how you think about, you know, strategy, product development, et cetera, et cetera. So being able to just plug your own models in, your own unique way of thinking to access that data, I think it's smart and I think it's good. And again, it's the democratization of this.

Lenny Murphy: And I love that. Yeah. Well, there's a, so I think variation on a theme, the next one, Mintel, their GMPD deep research from search and data to making confident decisions. They didn't talk about this being MCP based, but it's certainly the same, or meaning that my reading on this, some of you agree, is that they've made their data liquid and easy to access and utilize. They didn't talk about how they could also make that accessible within the customer's platform, but I expect that's next. But that whole idea of them realizing the value is in their data and making that more user-friendly, more accessible. I had somebody ask, I was from the CEO of a company this morning who asked me as part of the Simile news: should we be selling to Simile? Because they own their own ecosystem. And, you know, and the analogy used today, that company is Apple, right? You don't get to use their tools unless you're part of that system. So, and I point, I was like, well, I mean, I think I'd rather be in NVIDIA.

Kerry Hecht: So.

Lenny Murphy: Maybe it sells to everybody. And they have their ecosystem. NVIDIA's building their own stack, their own ecosystem, but everybody can use that. And I think that's the question for Nielsen's and Mintel and all these guys to think about if you can be Apple. You can force everybody into your ecosystem and own all of that. Or you just sell to everybody. You're making money one way or the other.

Kerry Hecht: Well, it's the next phase of syndicated research, really.

Lenny Murphy: Right. 100%.

Kerry Hecht: Yeah. So it's the next evolution of that. And it goes back to, you know, and there was some talk about this in all of these things that we're talking about today, you know, which is giving people, if this information is sort of publicly available in one way or another. Right? You kind of have to organize this stuff for them. And if syndicated research, if you own, or what you were saying before about big data, right? You know, so big data has been around for a long time. It's just, you haven't been able to do anything with it because the tools were not there to synthesize it across all of the different ways. You know, it's just too big of a rabbit hole. So I think that that's what we're seeing now. And, you know, it'll be interesting to think about. You know, what does this all ultimately funnel up to one big thing? You know, I mean, I don't know, which is kind of like the internet, I guess. You know, I mean, if we're, if we're taking a step back and you think about all of this data, surely it's gated at this point, gated through access, buying access to the data or buying access to the tool that accesses the data. But, you know, are you boxing yourself into a corner by keeping it separate from the broader from all the other pools that are pulling together.

Lenny Murphy: Well, so that is a good segue into our next big tech news, I think. And let's start with the last piece, right?

Kerry Hecht: Anthropic.

Lenny Murphy: So, Karley, we're skipping ahead just a little bit here in this section. The past few weeks, I'm sure you've been paying attention, the conversation has shifted, right? Of basically all the big tech companies saying, and like no we're the model's a commodity now um and we're not gonna spend a billion dollars in you know annually in supporting that when you're just gonna try and take away our business no screw you uh open weights where it goes open models open source uh be infrastructure let the model you know just be you know you shouldn't be spending all this money on the model very interesting shift from in self-serving.

Kerry Hecht: Now Anthropic came back. There's a lot to unpack there because I think that there's been rogue agents, right? It is now becoming rather commonplace that their tools are being built to strip out the guardrails on consumer models of this, which has its own. Wild set of implications. There are, you know, the hacking incidents are just going to become greater and probably more damaging and dangerous. But that cat's out of the bag. I mean, I think when these tools became several years ago at this point, when these tools became available for public consumption and there was huge adoption. I think that cat was out of the bag then. Now we're talking about it a little more. And I thought the thing that was interesting with Anthropic was, you know, when they were talking about, well, China's going to do this, and China's going to and China's going to do this. You know, it kind of made me sort of snicker a little bit. And like, and the United States doesn't do this. You're just like, why are we always trying to create an enemy in order to just say, like, we can talk about the problem without creating. A fake enemy, and having it be fear-driven, because the fear should be for everyone in the entire world about some guy in a basement that's deciding to make a biological weapon.

Lenny Murphy: Right. I mean, so I'll make a bet to you right now. SpaceX will open source Grok soon. It will be fully open source.

Kerry Hecht: Yeah. So. Yeah, but China to your point, right?

Lenny Murphy: We're these tools out there, plus, anybody in the U.S. can get a kidney or whatever, and you build the right ship sails.

Kerry Hecht: And I had so I had a funny conversation with um Arnis, who is my uh partner, and we were talking about peptides, right, which is a very gray area, and he was saying that his I've started taking this week, by the way. So, excellent. Um, so he was talking about how he couldn't get the right advice. From ChatGPT or Claude because they're like, sorry, I can't give you dosing advice. So he said, well, aren't there models there where we can strip away the guardrails? So we, about a month and a half ago, were sitting down and looking at what tools were available to strip the guardrails out of ChatGPT and Claude. And so again, I think we're like, that's my point: this is out of the bag. You know, two middle-aged people are sitting there trying to figure it out, you know, we're last, So, yeah. So, the cat is out of the bag. And we can create philosophical positions on this, but there's no way that the people who built these tools in the first place, you know, the cat was out of the bag for them 20 years ago.

Lenny Murphy: 100%. And the ultimate piece of this, right, is that the one. They are moving so fast, right? I mean, literally two weeks ago, you know, it's like, all right, what's my token investment? You know, I got to spend a billion dollars on tokens to now, like, screw that. No, no, that matters, right? And this idea of all that matters is the data and building tools. And AI is simply the mechanisms we use to build the tools to make use of that data. To drive better business outcomes and performance. And not saying that the frontier models are not valuable, but the economics of how it's been built has changed. And that ship sailed, it's changed. And we need to recognize that and start really building where real value accrues and value accrues, not in the model, but and be the if you're selling SaaS, right?

Kerry Hecht: I mean, you right, right, right. Well, because we're kind of talking it like there's there's sort of again, there's so many different angles to um this conversation. About what's valuable about these AI tools. And they are going to be use case specific, both from how you use it personally to how you use it for business and what businesses can do with it. And then there is going to be, I mean, again, there are always going to be bad actors. And so it's like, there's so many different angles. And I just don't think, I think, even if we wanted to be concerned about that or were concerned with it or are concerned with it. Again, the ship has kind of sailed, right?

Lenny Murphy: And you know, and the horse is out of the barn, right?

Kerry Hecht: Whatever. Even if governments agree on a set of rules like they have for cloning, for example, right? The nature of these tools is such that an individual does not necessarily have to function under the same set of ethical guidelines. And so.

Lenny Murphy: Need North Korea or Cuba or somewhere, they've cloned somebody. You know, that's happened. So they don't, you know, they didn't sign on.

Kerry Hecht: So it's probably happened everywhere, right? You know what I mean? And just, yeah, you know, so I mean, so I think that it's, it's just, I don't think we need to have, I don't know. I mean, yes, what they said was self-serving, but I thought it was really interesting that they were sort of pointing fingers elsewhere when you were just like, hold on a second. You know, every person on an individual level and every organization on an individual level has to come up with their own set of rules on this. And it's based on what they want to know and the convenience associated with it for them. And whether or not we want that to be true makes no difference. True.

Lenny Murphy: And I want to be clear that we're not calling out Anthropic, the news. These are bigger issues that we're all trying to work through. This becomes an example simply because they've been vocal about their position.

Kerry Hecht: Yeah, right. Well, they had the road agent. So there was a reason for them to, a reason for them to take a position on it that was what it is.

Lenny Murphy: And then so did OpenAI came out this week of like, oh, yeah, they had a couple that escaped, but right. I want to be conscious of time. Then we got a few more things we wanted to get through. I thought the Sequoia article on the next one trillion companies sells work, not software.

Kerry Hecht: There's the, you know, we've been talking about this, you know, thematically.

Lenny Murphy: And there's Sequoia saying, yep. Yes, I agree. There's the data.

Kerry Hecht: There's the infrastructure.

Lenny Murphy: Oh, there's the utility that makes the infrastructure work. And then there's actually, what the hell do you do with it?

Kerry Hecht: Yeah, there's the way of thinking, right? So it's right. The tools themselves. So, you know, again, we did touch on this and I'll move quickly, but like the tools themselves, now people can build these tools themselves, right? And they can build them in a way that is very specific to what their use case is. So they're not paying all kinds of extra money for things that they don't need, right? And so what you have to be selling is unique either. Access to data. I'll go back to what I said before: either access to data that they can't get somewhere else or a unique way of thinking that is different and adds value in a way that they presently don't know how to do. Um, and so I think that's what that was about.

Lenny Murphy: I think so too. And that ties directly into the other one, uh, that works it's went in reverse order. Um, the CMO is going away. Tied to more performance-driven titles around sales and development. And it's that same thing, it's shifting.

Kerry Hecht: Yeah, it's an evolution. And I saw it was funny because I was digging into this and I was like, so let's talk about the evolution of this because when I was thinking about. When I was a kid, you know, back in 1934, I don't think we had CMO roles then. So the C-suite was like, CFO, CEO, and maybe COO. So the chief marketing officer is not, it's not an old role anyway, right? And so they were talking, there's a long list of companies that have just abandoned this role and rolled it into chief strategy officer. Or lowered the threshold to where it's VP of marketing. But then there's companies that have done it that have brought them back. McDonald's was one that popped that it was like they eliminated the CMO role and brought it back. 

Lenny Murphy: So maybe it will be an industry-specific thing. Right. Well, and I think what it'll tie into, if these I have no problem, whatever you call the role. Yeah, right. A role that is responsible for tying from insights to activation, a business performance role. And I think what's been challenging for some of these roles was loosey-goosey KPIs. So, but we're getting better at the synthesis of information to be able to track attribution, right? And that's a marketing term, you know, delivering the right message to the right person at the right time that delivers the outcome and you can measure the outcome. Yes, right. So, and from that standpoint, I think that that is a marketing function. Sure. And the CMO will simply be more responsible for a very defined KPI around performance.

Kerry Hecht: What you just said made me wonder too. So if you think about the speed with which we're able to synthesize information now, I wonder if culturally we'll be so addicted to the speed of of answers, that it's almost like it's going to be a really challenging position in because you're be expecting the outcome of those things at the same speed. So it's like, hey, if you don't have this to me, and you know, if you don't have an answer for me and can show the ROI on this within two weeks, then we got to move on. You know, so I wonder if we're going to be giving things enough time to roost.

Lenny Murphy: That's a good point. And you go, we go all the way back to the beginning around simile, their thesis. Is to move at that speed, right? If you have a like, if you like the big data constant, you got the data coming in, we're going to model it, we're going to predict the outcome, all happening in real time.

Kerry Hecht: And well, you've got the flash points, right? So, like, the flash points. It makes me think of, you know, Erling from the World Cup and then Jiminy the raccoon. Right. So it's like, if you think about it, you know, they take over our collective consciousness, you know, for five minutes and then we move on. And if organizations are expecting the same thing to happen with product purchases or behavior changes or things like that, we might be in for a little bit of a bumpy road, or these folks might be in for a little bit of a bumpy road. Maybe.

Lenny Murphy: Well, that's a whole other. Conversation, right? If we could predict the new sphere, the zeitgeist, the collective consciousness, that's, some folks that have been trying to do that. So that's a whole other thing. But we can go, we can get really weird on that. Let's call out three just interesting readings. We don't necessarily have to get into these, but I thought these were interesting. Hopefully, our listeners will as well. This whole idea is on. And the profitability, et cetera, et cetera. Pay attention. I'm a fan of SpaceX. I think that all of these companies will do well eventually. But let's bear in mind, the business fundamentals are still kind of weird. And they're selling to each other. So that makes it even, you know, like NVIDIA is guaranteeing open AI with. A line of credit and SpaceX is selling to Google. And, it's like, yeah, it's like, is this like money laundering? You know, and I don't mean that literally, guys, don't get mad at me, but the economic cycles look different with these companies. 

Kerry Hecht: Well, and it's again, I go back to it so fast, right? So the speed with which things are happening is unbelievable. And the dollar amounts are unbelievable. And I think that both of those things feel like very uncharted territory for everybody. And so I think that how this shakes out eventually, I was sort of struggling to wrap my head around even a prediction on how this stuff shakes out eventually because it's like, you know, when you start talking about trillions of dollars, like, I don't even know what you're talking about, you know, right, right. Right.

Lenny Murphy: Yes. There's a cool DigiDay article on the hybrid approach to synthetic audience research.

Kerry Hecht: Yeah, this. I love this. Yeah.

Lenny Murphy: Building off, yeah, synthetic as a foundation and then doing real research and validation, you know, off of that.

Kerry Hecht: Well, and syndicated research, right? So it's again, it was one of the things that sort of got me thinking about how syndicated research is going to look different and be more interactive. And I think that this is pointing in that direction. I thought that that was a really smart article, and that the position they took on it was smart because it was, it's not, again, it's not when you talk about this stuff being relying on good data. If it's not just the data you collected in this very isolated incident, but it's building on all different kinds of things from social media listening to syndicated research, then yes, you are going to be able to build a much more robust program.

Lenny Murphy: Yep, agreed 100%. Yeah, so guys, check that article out. And then another article, I think we had one a week or two ago from MIT Sloan. That was in a similar vein of how Gen AI can and can't help manage customer insights. The real piece there was, look, yes, process, we can use Gen AI to limit process, but ultimately it's about the use and utilization and how people create value from the information across organization. The Gen AI can deliver it, but if somebody doesn't read it, they don't do anything with it. That's not. That's not on AI. That's on the human. And that's where the value really accrues. And I thought that was just a great point.

Kerry Hecht: Yeah, I couldn't agree more. I couldn't agree more. And I think that we are now seeing more and more examples of how people are able to articulate how they are using it and what value it is bringing, which we should all be paying attention to and learning from, because it'll shape the next generation of tools as well.

Lenny Murphy: Yep. Yep. All Kerry, I think just set the record on the longest exchange.

Kerry Hecht: Oh, sorry.

Lenny Murphy: No, no, no, no. I hope our listeners. This is, you know what? And everybody who listens, if you listen to us regularly, we try to keep it short and concise, but the reality is things are moving so fast and we are compounding knowledge, right? Yeah. We're trying to build context. We're trying to understand, separate the signal from the noise.

Kerry Hecht: That takes discussion. It's not just a bullet point.

Lenny Murphy: And that's the point. That's where this is, right? This is what we do is to try and make sense from a lot of complicated signals. And that's just fit in a 30-minute bucket. So thank you. Love this. Yes. For our listeners, we have a short list of guest hosts. When that pops up, Kerry is absolutely on that short list. You will be back. Probably pretty soon, actually. Yeah. Congratulations on the nuptials for your brother.

Kerry Hecht: I hope you have a great day. Oh, yeah. Thank you so much. Yeah. I'll pass that along to him. I appreciate it.

Lenny Murphy: Okay. Everybody. That is it for this edition of The Exchange.

Kerry Hecht: Thanks, guys. Thanks.

Links from the episode:

Kelly Beaver appointed Chief Executive Officer of Ipsos 

Vertus Group Acquires Welsh Research-Tech Firm Delineate 

Trooly Raises Nearly $20M Seed and Launches AI Research Platform for 45-Minute In-Depth Interviews 

Further Funds for Marketing Data Platform PolyBox 

Funds for Business Analytics Firm FireAI 

Discuss Launches Discuss Intelligence 

Nielsen Ad Intel AI Launch Heralds Major Shift 

Mintel Launches GNPD Deep Research 

Anthropic's Position on Open-Weights Models 

Sequoia: The Next $1T Company Sells Work, Not Software 

The Fortune 500 Is Deleting the CMO Title 

IPOs Test Investor Appetite for Unprofitable AI Giants 

Why Agencies Are Taking a Hybrid Approach to Synthetic Audience Research 

MIT Sloan: How GenAI Can and Can't Help Manage Customer Insights